A Comparative Study of PID Controller Tuning Using GA, EP, PSO and ACO

Proportional - Integral - Derivative control schemes continue to provide the simplest and effective solutions to most of the control engineering applications today. How ever PID controller are poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. This article comes up with a hybrid approach involving Genetic Algorithm (GA), Evolutionary Pro gramming (EP), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). The proposed hybrid algorithm is used to tune the PID parameters and its per formance has been compared with the conventional me thods like Ziegler Nichols and Cohen Coon method. The results obtained reflect that use of heuristic algorithm based controller improves the performance of process in terms of time domain specifications, set point tracking, and regulatory changes and also provides an optimum stability. Speed control of DC motor process is used to assess the efficacy of the heuristic algorithm methodology